Oncogenic drivers dictate immune control of acute myeloid leukemia

Acute myeloid leukemia (AML) is a genetically heterogeneous, aggressive hematological malignancy induced by distinct oncogenic driver mutations. The effect of specific AML oncogenes on immune activation or suppression is unclear. Here, we examine immune responses in genetically distinct models of AML and demonstrate that specific AML oncogenes dictate immunogenicity, the quality of immune response and immune escape through immunoediting. Specifically, expression of NrasG12D alone is sufficient to drive a potent anti-leukemia response through increased MHC Class II expression that can be overcome with increased expression of Myc. These data have important implications for the design and implementation of personalized immunotherapies for patients with AML.


REVIEWER COMMENTS
Reviewer #1 (Remarks to the Author): Manuscript by Austin et al entitled Oncogenic drivers dictate immune control of acute myeloid leukemia. Using distinct oncogenic models, the authors describe that specific AML oncogenes can dictate immunogenicity and immune response, which underlie immune evasion. The authors make use of retroviral murine overexpression models for NUP98-HOXA9+BCR-ABL, MLL-AF9, and AML1-ETO+NRasG12D. Transduced murine lin-BM cells are propagated in immunodeficient or immunocompetent mice and transformation trajectories are studied. The authors also make use of also of a transgenic NPMc/NRas12D model. In particular AML1-ETO+NRasG12D murine leukemic cells, as well as patient cells, express relatively high levels of MHC class II molecules potentially underlying the greater impact of the immune system on the delay of leukemia onset, and AML1-ETO+NRasG12D MHCII-/-cells were more efficient in inducing leukemia upon transplantation in immunocompetent mice. Leukemia cell intrinsic mechanisms also play a role since propagation of either AML1-ETO+NRasG12D or MLL-AF9 murine leukemic cells in immunocompetent mice resulted in the generation of more aggressive leukemia-inducing cells as compared to cells that were propagated in immunodeficient mice. Immunoedited cells were enriched for MYC signatures, which did not necessarily further drive intracellular proliferation programs but were rather considered to provide immune suppressive signals to the tumor microenvironment. Furthermore, clonal selection might also provide a role since immunoedited AML1-ETO+NRasG12D cells expressed reduced RAS transcriptional activity, coinciding with an upregulation of MHCII molecules. Ultimately, an increase in antigen presentation in AE/NRAS cells would result in T cell exhaustion. Overall, this is certainly interesting work describing the impact of specific oncogenes on immunogenicity and immune response making elegant use of immunodeficient and immunocompetent models. I do have a number of considerations, remarks and suggestions.
How do data described here in murine retroviral overexpression models relate to the situation in human patients? Oncogenes are overexpressed at relatively high levels, onset of leukemia is extremely fast, at least in some of the models (from 15-30 days to about 100 days in the AE/NRas model), and the effects of the immune system on the transformation process were evaluated in 2nd transplant models. It is suggested that "…a graded immune response to AML subtypes is specified by individual oncogenes", but it also appears as if timing plays an important role, whereby the faster the onset of disease (in immunodeficient models, so independent of immune evasion and most likely related to cell intrinsic mechanisms that drive aggressive proliferation, anti-apotosis, self-renewal and a differentiation block) the weaker the impact of the immune system. If eg NUP98-HOXA9/BCR-ABL cells were transplanted with much less cell numbers than 150k, which would result in slower onset of disease, would it not be conceivable that then also             C57BL/6J mice? To rule out timing effects, and to firmly establish that there are oncogene-specific mechanisms that control immunogenicity or immune evasion one would like to obtain somewhat more direct evidence showing eg how AML1-ETO, RAS, NH etc would differentially impact on eg MHCII expression. Fig 2B-C aims to put the association between oncogene expression and cell intrinsic immunogenicity in a human perspective, which is a nice addition. I do however wonder how easily these data can be generalized. For as far as I can see in various independent datasets the expression levels of HLA-DQA1 in human leukemias and normal stem/progenitor cells is quite diverse, with on average the highest expression in inv16 patients, but in fact in all genetic subgroups there appear to be patients that have either high or low expression of HLA-DQA1. And if anything, in most cases in most datasets there appear to be lower levels of HLA-DQA1 in AML compared to normal HSCs/MPPs. Regarding the single cell data taken from the van Galen paper: more details could have been provided. Which cells are actually analyzed and plotted in Fig.2s and Suppl. Fig.2C? All cells? Only the AML1-ETO translocated cells? One wonders why MHC II molecules would be upregulated in leukemic cells? This clearly would not provide any benefit. It has previously also been suggested that cell surface expression of HLA-DR,-DQ and -DP is in fact often lost on leukemia cells, due to downregulation of the HLA class II regulator CIITA. Earlier work also suggested that MHCII is epigenetically repressed in AML cells and that decitabine treatment would impair leukemogenesis by inducing more MHCII. While it is indeed true that in that Dufva et al paper (PMID: 32649887) it was suggested that, while in the majority of AML subgroups are HLAII low, AML harboring CBFB-MYH11 or RUNX1-RUNX1T1 translocations were characterized by higher HLA II expression and CIITA hypomethylation compared to other subtypes, it would be good to explore this in somewhat more detail. It is clear that differences exist between AML subtypes with regard to the level of downregulation of the antigen-presentation response, but whether this is truly increased in AML1-ETO cells compared to normal HSPCs and what the mechanistic link between AMl1-ETO, HLAII and possibly CIITA is remains unclear. Line 241: "These data reveal discrete effects of oncogenic drivers on immune regulatory molecule expression in AML cells, supporting a model whereby AE/NrasG12D AML has greater potential to interact with the immune system." Can we truly interpret this as a downstream consequence of oncogenic drivers? I think the authors could attempt to more thoroughly investigate the MHC class II landscape across multiple genetically distinct subgroups of AML patients and link this mechanistically to AML1-ETO. Furthermore, in the last part of the paper the authors go in great detail to study the T cell landscape in human AML1-ETO patients, but whether the described early T cell exhaustion is the consequence of enhanced antigen presentation is not immediately clear.

Data in
In Figure 2F it is shown that BA/NH had the highest expression of the immunosuppressive ligands PD-L1 and GAL-9 compared to MA9 and AE/NrasG12D, but I guess the authors then conclude that these factors are not dominant since no differences were seen in the transformation process of BA/NH transplanted cells in immunodeficient versus immunocompetent models? Also in the immunoediting experiments described in Fig.3, it is concluded that AML1-ETO+NRasG12D can undergo immunoediting when propagated in immunocompetent mice, but MLL-AF9 cells not. Again, the kinetics of leukemic onset in the MLL-AF9 model are significantly faster, and I wonder whether differences would exist when fewer MLL-AF9 cells were transplanted. Moreover, the transcriptional changes that were seen in immunoedited AML1-ETO+NRasG12D cells, were these signatures not seen in MLL-AF9 cells that were propagated in immunocompetent mice versus immunodeficient mice?
Besides retroviral overexpression models the authors also make use of a knockin NPMc/NRas12D model, and this model obviously does not suffer from potential non-physiological high level of oncogene expression. Intriguingly, in this model also no upregulation of H-2Db and MHC Class II molecules was observed, but there an upregulation of ligands with potential immunosuppressive function, PD-L1 and CD86, was observed. What would explain the difference between this knockin model with the AML1-ETO+NRasG12D retroviral model? Does RAS signal differently in the context of AML1-ETO vs NPMc? Does the expression level of RAS matter? It would be of interest to determine whether MHCII expression levels go up upon retroviral transduction with AE, NRASG12D or both, before transplantation in mice. Line 295: "…. we observed an inverse relationship between the variant allele frequency of mutant NRAS and the expression of multiple HLA (MHCII) genes, including HLA-DQA1, in NRAS-mutated human AML [41] (Fig. 3H, Supplementary Fig. S3F)". Since MHCII did not go down in IE AE/NRASG12D cells one wonders about the exact molecular pathways downstream of RAS that would drive immunogenicity, or whether more indirect mechanisms would be involved.  Austin et al provide a comprehensive and thorough description of how specific AML oncogenes either active or suppress the immune response. They demonstrate that specific AML oncogenes control immunogenicity and immune escape through immunoediting. They then show that immunoediting in AML is mediated through transcriptional plasticity, modulation of immunosuppressive molecules and clonal selection. Overall the claims of the paper are supported by convincing data in human and mouse model systems. Several concepts require additional clarification and further support.
-The majority of mouse AML data is generated by the retroviral transduction/transplantation approach, which can result in preferential viral incorporation into distinct progenitor cell states. To what degree are the differential responses to immune escapes mediated by the cell of origin rather than the oncogenic driver? -The authors suggest that the distinct responses to immune escape in the AML models are in part due to activated MYC. Can suppression of MYC rescue some of the observed phenotypes? -One of the most interesting observations is that increased MYC signaling and down-regulation of NRAS may contribute to immune escape. The authors should test this concept by suppressing MYC and reactivating the RAS-RAF-MEK pathway in an attempt to restore immune suppression.
-BA/NH express low levels of MHC class I genes along with high expression of immune check point ligands. What is the suspected mechanism for these specific gene changes? - Figure 1(E-G) -Is the disease manifestation in Rag2-/-and C57BL6 the same or different for each of the oncogenic drivers? In other words, is the type of AML similar in the two models? -Is there an explanation for why MA9 AML is delayed in C57BL6 (relative to Rag2-/-; Figure 1F) but not for BA/NH AML ( Figure 1E) even though both AMLs express similar levels of MHC genes ( Figure 2)? -The anti-PD1 data ( Figure 3M) is modest and highly variable.
Reviewer #3 (Remarks to the Author): Austin et al provide a comprehensive and high-quality manuscript. To my knowledge*, the data are technically sound, appropriately analysed and interpreted. Appropriate controls have been used. Their conclusions are sound and claims not overstated. Contextualization in introduction and discussion is excellent and accessible to a broad audience. The manuscript is very clearly written with enough detail to understand the experiments in nearly all places. They provide novel data on the relationship between oncogenic driver and immune control of AML and detailed studies to understand the mechanisms of immunogenicity and immune escape. As the authors point out, immune-directed therapies potentially do have a role in this disease, if used in combination and in the right circumstances. Therefore, this paper contains information important to advancing personalized therapy for AML *I do not have expertise in performing mouse experiments, so cannot comment on methodology of model generation/transfer and/or strain selection.
Key results are that immunocompetent mice survived longer in MA9 but especially in AE/NRas disease. This is accompanied by MHC class II expression higher on AE/NRas than MA9 in models, AML patients at bulk tumour and single cell level. Furthermore, AE/NRas AML generated on an MHC II background had shorter survival than when generated on a WT background. They authors found accelerated disease in immunocompetent mice with AE/NRas having previously passed through an immunocompetent (vs an immunodeficient host), accompanied by increased MYC expression, reduced NRas expression and reduced mutant NRas copy number. They established that NK/T depletion accelerated disease progression in AE/NRas and that AE/NRas in co-culture stimulated T cell proliferation. Differences in tumour environment T cells were not particularly marked but increase in CD8 Effector proportion in AE/Ras was noteworthy. Alterations in immunosuppressive molecule expression was found in AE/NRas CD8 T cells. scRNAseq data on immune-enriched AML1-ETO BM added detail and supported these observations. Specific points 1. Please make it a little clearer at the start of the results which mutations represent which risk category. Is there any reason these models of AML were chosen besides fitting into favourable, intermediate and adverse prognostic subclasses? Specifically, NUP98-HOXA9 is a rare translocation and I was curious why this was selected.
2. Why do you think it is that primary MA9 and AE/NRas mice survive 40-80 days post-transplant ( Fig S1B) but secondary mice also on a Rag2-/-yc-/-background survive 20 days ( Fig 1F) 5. The authors use a creative way to look at correlation between MYC overexpression and immune environment, but it requires more explanation and the correlation is not wholly convincing. It is clear where the score comes from (ref 39